Optimizing Project Time and Cost Prediction Using a Hybrid XGBoost and Simulated Annealing Algorithm

Optimizing Project Time and Cost Prediction Using a Hybrid XGBoost and Simulated Annealing Algorithm

Machine learning technologies have recently emerged as transformative tools for enhancing project management accuracy and efficiency. This study introduces a data-driven model that leverages the hybrid eXtreme Gradient Boosting-Simulated Annealing (XGBoost-SA) algorithm to predict the time and cost...

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Bibliographic Details
Main Authors: Ali Akbar ForouzeshNejad, Farzad Arabikhan, Shohin Aheleroff
Format: Article
Language:English
Published: MDPI AG 2024-11-01
Series:Machines
Subjects:
time forecasting
cost forecasting
extreme gradient boosting
simulated annealing
network complexity
Online Access:https://www.mdpi.com/2075-1702/12/12/867
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